• Asian-Australasian Journal of Animal Sciences
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• v.19 no.11
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• pp.1524-1528
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• 2006

A total of 437 animals, comprising lambs aged between 3 and 12 months and adults of either sex of Muzaffarnagari sheep maintained at the Central Institute for Research on Goats, Makhdoom, Farah, Mathura, India were screened to assess the prevalence of Haemonchus contortus infection following natural infection and to identify the various factors affecting faecal egg count (FEC) and packed cell volume (PCV) of ewes and their genetic control. The relationships between FEC, PCV and body weight were also estimated. The prevalence rate for H. contortus infection in the flock under study was 15.7% indicating much lower occurrence of worm infection in lambs up to one year of age. On the other hand, a large proportion i.e., 67.7% of sheep was refractive to natural H. contortus infection. The random effect of sire significantly contributed (p<0.01) variation in log-transformed FEC (LFEC) of ewes. The season of birth had a significant (p<0.01) effect on LFEC of ewes. The lactating ewes had significantly (p<0.01) higher faecal egg counts compared to dry and pregnant ewes. The linear regression effects of the age of ewes on LFEC of animals were significant (p<0.01) in the present study. The heritabilities of LFEC, PCV and body weights of ewes during the course of infection were moderate to high in magnitude and ranged from 0.24 to 0.47. The LFEC of ewes was significantly (p<0.05) and negatively correlated with PCV at both genetic and phenotypic level. The genetic and phenotypic relationships between LFEC and body weights of ewes were -0.26 and -0.06 for this breed. The genetic correlation of PCV and body weight of ewes was positive and high (0.58) and statistically significant (p<0.05) but it was negatively correlated (-0.01) with body weight at the phenotypic level.

• Korean Journal of Remote Sensing
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• v.38 no.4
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• pp.327-341
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• 2022

Cloud removal is often required to construct time-series sets of optical images for environmental monitoring. In regression-based cloud removal, the selection of an appropriate regression model and the impact analysis of the input images significantly affect the prediction performance. This study evaluates the potential of Gaussian process (GP) regression for cloud removal and also analyzes the effects of cloud-free optical images and spectral bands on prediction performance. Unlike other machine learning-based regression models, GP regression provides uncertainty information and automatically optimizes hyperparameters. An experiment using Sentinel-2 multi-spectral images was conducted for cloud removal in the two agricultural regions. The prediction performance of GP regression was compared with that of random forest (RF) regression. Various combinations of input images and multi-spectral bands were considered for quantitative evaluations. The experimental results showed that using multi-temporal images with multi-spectral bands as inputs achieved the best prediction accuracy. Highly correlated adjacent multi-spectral bands and temporally correlated multi-temporal images resulted in an improved prediction accuracy. The prediction performance of GP regression was significantly improved in predicting the near-infrared band compared to that of RF regression. Estimating the distribution function of input data in GP regression could reflect the variations in the considered spectral band with a broader range. In particular, GP regression was superior to RF regression for reproducing structural patterns at both sites in terms of structural similarity. In addition, uncertainty information provided by GP regression showed a reasonable similarity to prediction errors for some sub-areas, indicating that uncertainty estimates may be used to measure the prediction result quality. These findings suggest that GP regression could be beneficial for cloud removal and optical image reconstruction. In addition, the impact analysis results of the input images provide guidelines for selecting optimal images for regression-based cloud removal.

• Journal of the Korean Institute of Landscape Architecture
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• v.22 no.3
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• pp.29-40
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• 1994

The purpose of this study was to investigate factors and variables which have significant effects on satisfaction of urban pedestrian sidewalk in taejon city, and to suggest basic information for urban pedestrian sidewalk. These works consist of two phase; The first, tested the user's degree of satisfaction for 37 spots of pedestrian sidewalk slide and then selected 10 spots slide by the stratified random sampling method. The second, analyzed factors and variables of satisfaction of urban pedestrian sidewalk using the semantic differential scale method, and then processed by mean score, correlation, factor analysis, multiful algorithm. The results were summarized as follows; 1) The relationship between the man group and the woman group was highly correlated as well as between the student group.1 and the student group.2 hense these groups statistically showed no difference in satisfaction ratings. 2) Pedestrian sidewalk width, cleanness, pavement materials and construction condition can be significant variables of satisfaction of urban pedestrian sidewalk. 3) Factors covering the satisfaction of urban pedestrian sidewalk have been found to be Environment of pedestrian sidewalk, Vegetation of pedestrian sidewalk and Form of pedestrian sidewalk. By using the control method for the number of factors, C.P. has been obtained as 62.8%.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.1
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• pp.7-12
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• 2004

Real time ultrasonic measurements for 13th rib fat thickness (LBF), longissimus muscle area (LEMA) and marbling score (LMS) of live animal at pre-harvest and subsequent carcass measurements for fat thickness (BF), longissimus muscle area (EMA), marbling score (MS) as well as body weight of live animal, carcass weight (CW), dressing percentage (DP), and total merit index (TMI) on 755 Korean beef steers were analyzed to estimate genetic parameters. Data were analyzed using multivariate animal models with an EM-REML algorithm. Models included fixed effects for year-season of birth, location of birth, test station, age of dam, linear and quadratic covariates for age or body weight at slaughter and random animal and residual effects. The heritability estimates for LEMA, LBF and LMS on RTU scans were 0.17, 0.41 and 0.55 in the age-adjusted model (Model 1) and 0.20, 0.52 and 0.55 in the weight-adjusted model (Model 2), respectively. The Heritability estimates for subsequent traits on carcass measures were 0.20, 0.38 and 0.54 in Model 1 and 0.23, 0.46 and 0.55 in Model 2, respectively. Genetic correlation estimate between LEMA and EMA was 0.81 and 0.79 in Model 1 and Model 2, respectively. Genetic correlation estimate between LBF and BF were high as 0.97 in Model 1 and 0.98 in Model 2. Real time ultrasonic marbling score were highly genetically correlated to carcass MS of 0.89 in Model 1 and 0.92 in Model 2. These results indicate that RTU scans would be alterative to carcass measurement for genetic evaluation of meat quality in a designed progeny-testing program in Korean beef cattle.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.9
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• pp.1227-1232
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• 2008

Carcass characteristics data of Hanwoo (N = 1,084) were collected from two stations of the National Livestock Institute of Animal Science (NIAS), Korea and records from thirteen individual cow-calf operators were analyzed to estimate variance and covariance components and the effect of different slaughter endpoints. Carcass traits analyzed were cold carcass weight (CWT, kg), REA (rib eye area, cm2), back fat thickness (mm) and marbling score (1-7). Four different models were examined. All models included sex and contemporary group as fixed effects and the animal's direct genetic potential and environment as random effects. The first model fitted a linear covariate of age at slaughter. The second model fitted both linear and quadratic covariates of age at slaughter. The third model fitted a linear covariate of body weight at slaughter. The fourth model fitted both linear covariates of age at slaughter and body weight at slaughter. Variance components were estimated using the REML procedure with Gibb's sampler. Heritability estimate of CWT was in the range of 0.08-0.11 depending on the model applied. Heritability estimates of BF, REA and MS were in the ranges of 0.23-0.28, 0.19-0.26, and 0.44-0.45, respectively. Genetic correlations between CWT and BF, between CWT and REA, and between CWT and MS were in the ranges of -0.33 - -0.14, 0.73-0.84, and -0.01- 0.11, respectively. Genetic correlations between REA and BF, between MS and BF and between REA and MS were in the ranges of -0.82 ~ -0.72, 0.04~0.28 and -0.08 ~ -0.02, respectively. Variance and covariance components estimated varied by model with different slaughter endpoints. Body weight endpoint was more effective for direct selection in favor of yield traits and body weight endpoints affected more of the correlated response to selection for the traits of yield and quality of edible portion of beef.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.231-239
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• 2015

A Poisson model is the first choice for counts data. Quasi Poisson or negative binomial models are usually used in cases of over (or under) dispersed data. However, these models might be unsuitable if the data consist of excessive number of zeros (zero inflated data). For zero inflated counts data, Zero Inflated Poisson (ZIP) or Zero Inflated Negative Binomial (ZINB) models are recommended to address the issue. In this paper, we further considered a situation where zero inflated data are spatially correlated. A mixed effect model with random effects that account for spatial autocorrelation is used to fit the data.

• Journal of The Korean Society of Integrative Medicine
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• v.10 no.4
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• pp.49-56
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• 2022

Purpose : The purpose of this study was to examine the effects of the motivation for choosing a major, COVID-19 anxiety, and work values on the employment preparation behavior of health college students and to provide evidence for developing programs for employment preparation behavior in the future. Methods : Employing a random sampling method, a survey was conducted from April 22 to June 3, 2022, using an electronically-disseminated questionnaire with college students majoring in medical technician, health administration, and nursing from D and K colleges located in Daegu. A total of 402 students who fully understood and agreed to the purpose of the study participated. The SPSS statistical program was used to analyze the collected data, which were verified using correlation and regression analyses. Results : The results of the study are: First, employment preparation behavior was positively correlated to major selection motivation, COVID-19 anxiety, and work values. Second, significant relationships were found between employment preparation behavior and motivation behind choosing a major, work values, and COVID-19 anxiety, in that order. The higher the major selection motivation, work values, and COVID-19 anxiety were, the better the employment preparation behavior was. Conclusion : The study's results indicate that it would be meaningful to provide health college students who were highly motivated to select their major and who possess sound work values with well-prepared job training programs. Various activities organized by the school for improving the students' self-satisfaction and self-efficacy, which can strengthen their long-term work values, could also be provided. In addition, due to the continuing COVID-19 pandemic, college students may feel anxious about new infectious diseases that might occur in the future. Therefore, considering the contemporary situation, a helpful educational program will be invaluable to fit the pupils for life's battle after they finish their education.

• Economic Analysis
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• v.27 no.1
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• pp.37-66
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• 2021

This paper examines the potential impacts of COVID-19 on poverty in ASEAN countries. The first estimate, adopted from Summer et al. (2020) and Nonvide (2020), configures three scenarios of contractions in per capita household income or consumption; the impact of each scenario on poverty is calculated using poverty lines at different thresholds. In the second estimate, poverty impacts in 2020 and 2021 were projected using regression models controlling for unobserved country effects, unbalanced data, and endogeneity. COVID-19 has been shown to have negative impacts on poverty reduction in the ASEAN Member States. To reduce poverty, concerted efforts are needed to implement policies for reducing income inequality and promoting economic growth. Such efforts will not only speed up the countries' return to pre-pandemic poverty levels but also contribute to further accelerating poverty reduction.

• Journal of Preventive Medicine and Public Health
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• v.37 no.4
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• pp.381-389
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• 2004

Objective : To compare the efficacy between SKI306X and Diclofenac by using generalized estimating equations (GEE) methodology in the analysis of correlated bivariate binary outcome data in Osteoarthritis (OA) diseases. Methods : A randomized, double-blind, active comparator-controlled, non-inferiority clinical trial was conducted at 5 institutions in Korea with the random assignment of 248 patients aged 35 to 75 years old with OA of the knee and clinical evidence of OA. Patients were enrolled in this study if they had at least moderate pain in the affected knee joint and a score larger than 35mm as assessed by VAS (Visual Analog Scale). The main exposure variable was treatment (SKI 306X vs. Diclofenac) and other covariates were age, sex, BMI, baseline VAS, center, operation history (Yes/No), NSAIDS (Y/N), acupuncture (Y/N), herbal medicine (Y/N), past history of musculoskeletal disease (Y/N), and previous therapy related with OA (Y/N). The main study outcome was the change of VAS pain scores from baseline to the 2nd and 4th weeks after treatment. Pain scores were obtained as baseline, 2nd and 4th weeks after treatment. We applied GEE approach with empirical covariance matrix and independent(or exchangeable) working correlation matrix to evaluate the relation of several risk factors to the change of VAS pain scores with correlated binary bivariate outcomes. Results : While baseline VAS, age, and acupuncture variables had protective effects for reducing the OA pain, its treatment (Joins/Diclofenac) was not statistically significant through GEE methodology (ITT:aOR=1.37, 95% CI=(0.8200, 2.26), PP:aOR=1.47, 95% CI=(0.73, 2.95)). The goodness-of-fit statistic for GEE (6.55, p=0.68) was computed to assess the adequacy of the fitted final model. Conclusions : Both ANCOVA and GEE methods yielded non statistical significance in the evaluation of non-inferiority of the efficacy between SKI306X and Diclofenac. While VAS outcome for each visit was applied in GEE, only VAS outcome for the fourth visit was applied in ANCOVA. So the GEE methodology is more accurate for the analysis of correlated outcomes.

• Journal of Animal Science and Technology
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• v.54 no.1
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• pp.9-14
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• 2012

The purpose of this study was to estimate heritabilities and genetic correlations for reproductive and productive traits and to apply their estimates to selection strategies in a swine population. Reproductive and productive traits considered in this study were number of born alive piglet (NBA), number of weaned piglet (NW), loin eye area (LEA), days to 90 kg (D90KG), back fat thickness (BF), and lean meat content (LEAN). Data were collected from 9,886 litters on 2,447 sows for reproductive traits and 10,181 gilts and boars for productive traits from Jan. 2000 to Dec. 2008 in a swine GGP farm. The statistical model to estimate genetic parameters for considering traits was a multiple traits animal model with including animal and maternal additive effects and litter effects on reproductive traits and animal additive effects on productive traits as random as well as some of fixed effects. For estimating (co) variance components of several random effects, restricted maximum likelihood methodology was used on this assumed model. The estimated heritabilities by animal additive effects and maternal effects were 0.07 and 0.02 for NBA and 0.03 and 0.02 for NW, respectively. Genetic correlation estimate for direct genetic effects between NBA and NW was 0.14. Heritability estimates for direct genetic effects were 0.19, 0.39, 0.36, and 0.43 for LEA, D90KG, BF and LEAN, respectively. The genetic correlation of LEA with LEAN was 0.35. Productive traits were antagonistically correlated with reproductive traits. From these results it is concluded that, if selection is done for strong positive effects of reproductive traits, then this would decline productive performance.